DocumentCode
67623
Title
A Hyper-Heuristic Scheduling Algorithm for Cloud
Author
Chun-Wei Tsai ; Wei-Cheng Huang ; Meng-Hsiu Chiang ; Ming-Chao Chiang ; Chu-Sing Yang
Author_Institution
Dept. of Appl. Inf. & Multimedia, Chia Nan Univ. of Pharmacy & Sci., Tainan, Taiwan
Volume
2
Issue
2
fYear
2014
fDate
April-June 1 2014
Firstpage
236
Lastpage
250
Abstract
Rule-based scheduling algorithms have been widely used on many cloud computing systems because they are simple and easy to implement. However, there is plenty of room to improve the performance of these algorithms, especially by using heuristic scheduling. As such, this paper presents a novel heuristic scheduling algorithm, called hyper-heuristic scheduling algorithm (HHSA), to find better scheduling solutions for cloud computing systems. The diversity detection and improvement detection operators are employed by the proposed algorithm to dynamically determine which low-level heuristic is to be used in finding better candidate solutions. To evaluate the performance of the proposed method, this study compares the proposed method with several state-of-the-art scheduling algorithms, by having all of them implemented on CloudSim (a simulator) and Hadoop (a real system). The results show that HHSA can significantly reduce the makespan of task scheduling compared with the other scheduling algorithms evaluated in this paper, on both CloudSim and Hadoop.
Keywords
cloud computing; knowledge based systems; scheduling; CloudSim; HHSA; Hadoop; cloud computing systems; hyper-heuristic scheduling algorithm; rule-based scheduling algorithms; Cloud computing; Heuristic algorithms; Pricing; Scheduling algorithms; Time complexity; Cloud computing; and Hadoop; evolutionary algorithm; scheduling;
fLanguage
English
Journal_Title
Cloud Computing, IEEE Transactions on
Publisher
ieee
ISSN
2168-7161
Type
jour
DOI
10.1109/TCC.2014.2315797
Filename
6784130
Link To Document